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Cell · 2025

Simplifying protein engineering with deep learning.

Cell, 188(17): 4477-4479 PMID 40845808 DOI 10.1016/j.cell.2025.07.037

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Аннотация

When it comes to deep learning for protein engineering, there is strength in simplicity. In this issue of Cell, through thoughtful deployment of existing fixed-backbone sequence design models, Caixia Gao and colleagues engineer diverse genome editing systems with improved functionality, enabling powerful capabilities in fine-grained and large-scale genome editing as demonstrated through strong experimental validation.

Цитирование